Development, Quantification, and Demonstration of the Occupancy-Based Controls for Smart and Healthy Buildings

Abstract

The heating, ventilation, and air-conditioning (HVAC) system consumes a significant fraction of building energy to maintain satisfactory indoor air quality (IAQ) and thermal comfort conditions for its occupants. Occupancy-based control (OBC) is attracting significant research interest since it could address the contradiction between the goals of reducing building energy consumption and maintaining occupants’ needs (e.g., thermal comfort). This research aims to investigate and validate the role of occupancy-based HVAC controls in smart and healthy buildings regarding energy efficiency and infection risk mitigation. First, this study develops a nationwide building energy simulation suite to quantify energy savings of occupancy-based HVAC controls. Multiple levels of diversities are considered in this simulation suite, including building types, climate zones, etc. Second, a cost-effectiveness analysis framework is established to quantify monetary savings. Third, field testing is conducted in real commercial and residential buildings to validate and evaluate the energy saving of OBC. The impact on occupants’ thermal comfort is also investigated and discussed. Last, a smart carbon dioxide (CO2) based ventilation algorithm is developed to mitigate the infection risk of COVID-19 in buildings while maintaining relatively good energy performance. The results suggest that in general, occupancy sensors demonstrate great energy-saving potential, especially for the buildings with densely occupied spaces and dynamic occupancy schedules. Many factors influence the energy-saving potential of OBC in commercial and residential buildings, among which the climate zone play the dominant role. For commercial buildings, the 30% HVAC energy-saving goal is tangible on a nationwide scale; while for residential buildings, applying a temperature setback during the unoccupied period is not likely to achieve 30% HVAC energy savings nationally. Second, the cost-effectiveness analysis shows that although the HVAC energy savings of OBCs are substantial, the actual cost-effectiveness is not that satisfactory. Occupant-counting sensors' economic performance (measured by discounted payback period) in commercial buildings highly depends on the building type. It is recommended to implement occupant counting sensors only for the most densely occupied zones in commercial buildings to reduce the costs and achieve a DPB shorter than five years. For residential buildings, it’s hard to achieve a shorter-than-two-year DPB for many climate zones by simply applying temperature setback control. Third, the field testing results suggest that the HVAC energy-saving ratio in real building operation basically matches the computer simulation. The sensor accuracy and occupant behaviors also play a dominant role in the energy-saving ratio of OBC. Besides, results show that the implementation of OBC did not affect the occupant’s comfort too much in the daytime but could not achieve good temperature control in the nighttime due to high false negative issues. Last, the proposed smart ventilation control algorithm allows building operators to flexibly secure the building operation safety based on the preset maximum infection risk level, so the balance between energy efficiency and infection risk mitigation is maintained. The results show that the proposed control reduces the infection risk by more than a half compared with traditional outdoor airflow fraction based mitigation measures and achieves higher energy efficiency performance.